How to Lie with Statistics

How Does He Know?

Percentages offer a fertile field for confusion. And like the ever-impressive decimal they can lend an aura of precision to the inexact.

Author Louis Bromfield is said to have a stock reply to critical correspondents when his mail becomes too heavy for individual attention. Without conceding anything and without encouraging further correspondence, it still satisfies almost everyone. The key sentence: “There may be something in what you say.”

The test of the random sample is this: Does every name or thing in the whole group have an equal chance to be in the sample? The purely random sample is the only kind that can be examined with entire confidence by means of statistical theory, but there is one thing wrong with it. It is so difficult and expensive to obtain for many uses that sheer c

To say “almost one and one-half” and to be heard as “three”—that’s what the one-dimensional picture can accomplish.

The fallacy is an ancient one that, however, has a powerful tendency to crop up in statistical material, where it is disguised by a welter of impressive figures. It is the one that says that if B follows A, then A has caused B.

Not all the statistical information that you may come upon can be tested with the sureness of chemical analysis or of what goes on in an assayer’s laboratory. But you can prod the stuff with five simple questions, and by finding the answers avoid learning a remarkable lot that isn’t so. Who Says So?

What’s Missing?

So when you see an average-pay figure, first ask: Average of what? Who’s included?